Parameter Recovery of the Explanatory Multidimensional Rasch Model. (Paperback)
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Von Händler/Antiquariat, The Book Depository [54837791], Gloucester, UK, United Kingdom.
Brand New Book ***** Print on Demand *****.Enjoy a wide range of dissertations and theses published from graduate schools and universities from around the world. Covering a wide range of academic topics, we are happy to increase overall global access to these works and make them available outside of traditional academic databases. These works are packaged and produced by BiblioLabs under license by ProQuest UMI. The description for these dissertations was produced by BiblioLabs and is in no way affiliated with, in connection with, or representative of the abstract meta-data associated with the dissertations published by ProQuest UMI. If you have any questions relating to this particular dissertation, you may contact BiblioLabs directly.

Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
This item is printed on demand. Paperback. Recently, there have been two types of model formulations used to demonstrate the utility of explanatory item response models. Specifically, the generalized linear mixed model (GLMM) and hierarchical generalized linear model (HGLM) have expanded item response models to include covariates for item effects, person effects, or both simultaneously. Both frameworks have recently been garnering greater attention in the educational measurement field. Despite these two frameworks being conceptually equivalent, much of the related literature has emphasized one or the other. However, to date, there has been little attempt to associate the frameworks together. In addition, item response models that have been described within the GLMM and HGLM frameworks have mostly been of the unidimensional type. Very little has been done to demonstrate the utility of an explanatory multidimensional item response model. As explanatory models become more prevalent in research and practice, it is important to maintain software that can estimate them. SAS is an all-purpose and widely-used program that can estimate explanatory item response models. However, no previous research has examined how well SAS can recover the parameters of an explanatory multidimensional Rasch model (EMRM). There were three main goals of this study. First, several types of Rasch models, including both non-explanatory and explanatory models, were summarized within the GLMM and HGLM frameworks. The equivalence of these two frameworks was demonstrated for each model. Second, a parameter recovery study was performed to determine how well SAS PROC NLMIXED can recover the parameters of an EMRM. The effect of sample size and test length on parameter recovery was assessed. The results of the simulation study indicate that very little bias occurs, even with small sample sizes and short test lengths. The final goal was to demonstrate the utility of an EMRM model using empirical data. Using data collected from the Marlowe-Crowne Social Desirability Scale (MCSDS), an EMRM was fit to the data while using gender as a covariate. Interpretations of the model parameter estimates were given and it was concluded that gender did not explain a significant amount of variation in either of the MCSDS subscales. This item ships from La Vergne,TN.

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Enjoy a wide range of dissertations and theses published from graduate schools and universities from around the world. Covering a wide range of academic topics, we are happy to increase overall global access to these works and make them available outside of traditional academic databases. These works are packaged and produced by BiblioLabs under license by ProQuest UMI. The description for these dissertations was produced by BiblioLabs and is in no way affiliated with, in connection with, or representative of the abstract meta-data associated with the dissertations published by ProQuest UMI. If you have any questions relating to this particular dissertation, you may contact BiblioLabs directly. Paperback, Label: ProQuest, UMI Dissertation Publishing, ProQuest, UMI Dissertation Publishing, Produktgruppe: Book, Publiziert: 2011-09-03, Studio: ProQuest, UMI Dissertation Publishing.

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J Carl Setzer, Paperback, English-language edition, Pub by BiblioLabsII.